

   As I think there have been problems with the attachments, I've uploaded the jpeg graphs to megaupload:

   http://www.megaupload.com/?d=M2WXA9Z0

   http://www.megaupload.com/?d=NWCPUY1C

   Best wishes.  Iker



________________________________

Para: r-sig-mixed-models <r-sig-mixed-models@r-project.org>
Enviado: martes 27 de septiembre de 2011 19:51
Asunto: [R-sig-ME] Gamma transformation



   Dear list: 


   After implementing a model, I tested it for homocedasticity, and I was not actually very happy, as the variance seems to increase for higher values, according to the fitted values vs. residuals plot (attached - "Unmodified"). I tried to log-transform the response variable, but the result was similar. After looking for possible transformations of the response variable, I found that "gamma(x)" worked really well, and stabilized the variance of the model for all the range when plotting the fitted values vs residuals (attached - "Gamma"). 


   I am happy with that, but it's just that I would like to make sure wether this is a correct step, and if it's possible, know what is the reason why this happens when applying that transformation. I am not an expert but I would really like to try to learn something more about this. I have tried to find some information in the web, but I'm not very happy with it. Obviously, only if you have the time and the willingness to explain it, or help me find some information about it. I appreciate it very much in any case.

   Than you very much.

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